The IIoT Revolution: What's Really Going to Change?

Plant Workers

In my last two posts about the Industrial Internet of Things (IIoT), I’ve discussed the importance of finding a common IIoT definition, and the four key pillars of technology capabilities that form the IIoT platform.

But I think what everyone really wants to know is how IIoT will help them in the real world—what specifically will change in their day-to-day activities and operations that will result in faster and more accurate information, new operational capabilities and, ultimately, an improvement in the bottom line.

So, in this post I want to take a closer look at how IT-OT convergence is causing a revolution in OT. The resulting information explosion is shifting how manufacturers derive value from shop floor assets, and the ability to not only automate processes but provide new analytics and insight will transform business.

Operational technology: The old school of thought

Traditionally, operational technology (OT) has provided its primary value in automating and optimizing a process (this is mostly still the case). Take the example of a chocolate manufacturer. With the use of motors, drives, sensors and controllers we can now run filling and packaging machines at rates of more than 1,000 pieces per minute. Such automation has reduced labor costs, increased throughput, and improved safety and product quality.

This example rings true across many different industries and the value has been clear. Over time, these machines have slowly been integrated with other software applications to drive additional benefits, like PLM for recipe management or MES for traceability, but this has generally been a slow process and has not created the explosion in additional data and value being promised by the IIoT.

“A pump is no longer just a pump”

As I alluded to in the last post, the traditional ISA-95/Purdue model that has traditionally separated business operations from manufacturing operations is starting to change. While there is still some delineation of what role equipment, automation and software applications have within an enterprise, the lines are blurring. The hierarchy and siloed nature of the information is quickly becoming a thing of the past, as the IIoT is allowing a web of communication between all “things” in the enterprise.

Take the same controllers used by the chocolate manufacturer in the prior example. They still control the speed, amount and frequency of materials used in production. But by using IIoT technology, the data from the controller is no longer just used to control the production process in a hierarchical manner. The additional data like temperature, vibration, flow, and more may be directly used by the Big Data Analytics capabilities of an Asset Performance Management (APM) application to predict the likelihood of future failures and trigger the appropriate maintenance activities based on the risk and criticality of the specific asset in question. And this is not limited to reliability; this same info might also trigger an EHS alert to operators as well as connect to ERP and financial systems for traceability or real time profitability analysis. Suddenly a piece of information that could only be used immediately in a certain way is free to be plucked and contextualized for use from whatever business or operational system that’s been empowered to do so. 

This collapse of informational hierarchy and explosion of data relevance and usefulness speaks right to the wants and needs of manufacturers today. The following chart represents responses from more than 500 global manufacturers on what they hope to accomplish with their OT stack. 

Top OT Objectives

As you can see, having accurate, relevant and actionable data rules the day, and with the way IIoT is transforming the interaction between business, IT and operational systems, it will be the biggest enabler of this objective. Moreover, it is directly relevant to just about every other objective listed on this chart.

It’s not longer a question of if your company will start using the information coming from OT to make better decisions, but if your company will make the move before your competitors.

Matthew Littlefield's picture

Matthew Littlefield

Matthew Littlefield co-founded LNS Research in 2011. In his current role as President and Principal Analyst, he oversees LNS’s coverage of the industrial value chain. A recognized industry expert, Matthew contributes to the widely read LNS Research blog, GE's Intelligent Platforms Industrial Internet blog and many other industry publications. 

More Posts

Add new comment